Interstitial water temperature within spawning habitats of salmonids may differ from surface-water temperature depending on intragravel flow paths, geomorphic setting, or presence of groundwater. Because survival and developmental timing of salmon are partly controlled by temperature, monitoring temperature within gravels used by spawning salmonids is required to adequately describe the environment experienced by incubating eggs and embryos. Here we describe a simple method of deploying electronic data loggers within gravel substrates with minimal alteration of the natural gravel structure and composition. Using data collected in spawning sites used by summer and fall chum salmon Oncorhynchus keta from two streams within the Yukon River watershed, we compare contrasting thermal regimes to demonstrate the utility of this method.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/032012-JFWM-025","usgsCitation":"Zimmerman, C.E., and Finn, J.E., 2012, A simple method for in situ monitoring of water temperature in substrates used by spawning salmonids: Journal of Fish and Wildlife Management, v. 3, no. 2, p. 288-295, https://doi.org/10.3996/032012-JFWM-025.","productDescription":"8 p.","startPage":"288","endPage":"295","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026489","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":474231,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/032012-jfwm-025","text":"Publisher Index Page"},{"id":296920,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2b21e4b08de9379b3266","contributors":{"authors":[{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":537209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, James E.","contributorId":11157,"corporation":false,"usgs":true,"family":"Finn","given":"James","email":"","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":537353,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70041045,"text":"70041045 - 2012 - A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions","interactions":[],"lastModifiedDate":"2017-04-06T14:41:10","indexId":"70041045","displayToPublicDate":"2012-11-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions","docAbstract":"Spatially explicit representations of vegetation canopy height over large regions are necessary for a wide variety of inventory, monitoring, and modeling activities. Although airborne lidar data has been successfully used to develop vegetation canopy height maps in many regions, for vast, sparsely populated regions such as the boreal forest biome, airborne lidar is not widely available. An alternative approach to canopy height mapping in areas where airborne lidar data is limited is to use spaceborne lidar measurements in combination with multi-angular and multi-spectral remote sensing data to produce comprehensive canopy height maps for the entire region. This study uses spaceborne lidar data from the Geosciences Laser Altimeter System (GLAS) as training data for regression tree models that incorporate multi-angular and multi-spectral data from the Multi-Angle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging SpectroRadiometer (MODIS) to map vegetation canopy height across a 1,300,000 km2 swath of boreal forest in Interior Alaska. Results are compared to in situ height measurements as well as airborne lidar data. Although many of the GLAS-derived canopy height estimates are inaccurate, applying a series of filters incorporating both data associated with the GLAS shots as well as ancillary data such as land cover can identify the majority of height estimates with significant errors, resulting in a filtered dataset with much higher accuracy. Results from the regression tree models indicate that late winter MISR imagery acquired under snow-covered conditions is effective for mapping canopy heights ranging from 5 to 15 m, which includes the vast majority of forests in the region. It appears that neither MISR nor MODIS imagery acquired during the growing season is effective for canopy height mapping, although including summer multi-spectral MODIS data along with winter MISR imagery does appear to provide a slight increase in the accuracy of resulting height maps. The finding that winter, snow-covered MISR imagery can be used to map canopy height is important because clear sky days are nearly three times as common during the late winter period as during the growing season. The increased odds of acquiring cloud-free imagery during the target acquisition period make regularly updated forest height inventories for Interior Alaska much more feasible. A major advantage of the GLAS–MISR–MODIS canopy height mapping methodology described here is that this approach uses only data that is freely available worldwide, making the approach potentially applicable across the entire circumpolar boreal forest region.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2012.02.020","usgsCitation":"Selkowitz, D.J., Green, G., Peterson, B.E., and Wylie, B., 2012, A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions: Remote Sensing of Environment, v. 121, p. 458-471, https://doi.org/10.1016/j.rse.2012.02.020.","productDescription":"14 p.","startPage":"458","endPage":"471","ipdsId":"IP-035645","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":263516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263515,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2012.02.020"}],"volume":"121","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d59e83e4b0ba654692b9b6","contributors":{"authors":[{"text":"Selkowitz, David J. 0000-0003-0824-7051 dselkowitz@usgs.gov","orcid":"https://orcid.org/0000-0003-0824-7051","contributorId":3259,"corporation":false,"usgs":true,"family":"Selkowitz","given":"David","email":"dselkowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":469248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Green, Gordon","contributorId":65738,"corporation":false,"usgs":true,"family":"Green","given":"Gordon","email":"","affiliations":[],"preferred":false,"id":469250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Birgit E. 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":3599,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","middleInitial":"E.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":469249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wylie, Bruce 0000-0002-7374-1083","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":107996,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","affiliations":[],"preferred":false,"id":469251,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70041248,"text":"ds709D - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:11:27","indexId":"ds709D","displayToPublicDate":"2012-11-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"D","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Takhar mineral district, which has placer gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for North Takhar) and the WGS84 datum. The final image mosaics were subdivided into nine overlapping tiles or quadrants because of the large size of the target area. The nine image tiles (or quadrants) for the North Takhar area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709D","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme File; 2 Maps: 11 x 8.5 and 41.76 x 48.21 inches; 18 Image Files: 18 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709D.","productDescription":"Readme File; 2 Maps: 11 x 8.5 and 41.76 x 48.21 inches; 18 Image Files: 18 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-032347","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":263529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_D.jpg"},{"id":263609,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/d/index_maps/North_Takhar_Image_Index_Map.pdf"},{"id":263610,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/d/image_files/image_files.html"},{"id":263611,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/d/metadata/metadata.html"},{"id":263612,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/d/shapefiles/shapefiles.html"},{"id":263613,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"},{"id":263606,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/d/"},{"id":263607,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/d/1_readme.txt"},{"id":263608,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/d/index_maps/North_Takhar_Area-of-Interest_Index_Map.pdf"}],"country":"Afghanistan","otherGeospatial":"North Takhar","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.5,29.25 ], [ 60.5,38.5 ], [ 75.0,38.5 ], [ 75.0,29.25 ], [ 60.5,29.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bfbdabe4b01744973f7817","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":469453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":469454,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188518,"text":"70188518 - 2012 - Characterizing post-drainage succession in Thermokarst Lake Basins on the Seward Peninsula, Alaska with TerraSAR-X Backscatter and Landsat-based NDVI data","interactions":[],"lastModifiedDate":"2017-06-14T14:12:02","indexId":"70188518","displayToPublicDate":"2012-11-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing post-drainage succession in Thermokarst Lake Basins on the Seward Peninsula, Alaska with TerraSAR-X Backscatter and Landsat-based NDVI data","docAbstract":"Drained thermokarst lake basins accumulate significant amounts of soil organic carbon in the form of peat, which is of interest to understanding carbon cycling and climate change feedbacks associated with thermokarst in the Arctic. Remote sensing is a tool useful for understanding temporal and spatial dynamics of drained basins. In this study, we tested the application of high-resolution X-band Synthetic Aperture Radar (SAR) data of the German TerraSAR-X satellite from the 2009 growing season (July–September) for characterizing drained thermokarst lake basins of various age in the ice-rich permafrost region of the northern Seward Peninsula, Alaska. To enhance interpretation of patterns identified in X-band SAR for these basins, we also analyzed the Normalized Difference Vegetation Index (NDVI) calculated from a Landsat-5 Thematic Mapper image acquired on July 2009 and compared both X-band SAR and NDVI data with observations of basin age. We found significant logarithmic relationships between (a) TerraSAR-X backscatter and basin age from 0 to 10,000 years, (b) Landat-5 TM NDVI and basin age from 0 to 10,000 years, and (c) TerraSAR-X backscatter and basin age from 50 to 10,000 years. NDVI was a better indicator of basin age over a period of 0–10,000 years. However, TerraSAR-X data performed much better for discriminating radiocarbon-dated basins (50–10,000 years old). No clear relationships were found for either backscatter or NDVI and basin age from 0 to 50 years. We attribute the decreasing trend of backscatter and NDVI with increasing basin age to post-drainage changes in the basin surface. Such changes include succession in vegetation, soils, hydrology, and renewed permafrost aggradation, ground ice accumulation and localized frost heave. Results of this study show the potential application of X-band SAR data in combination with NDVI data to map long-term succession dynamics of drained thermokarst lake basins.
","language":"English","publisher":"Remote Sensing","doi":"10.3390/rs4123741","usgsCitation":"Regmi, P., Grosse, G., Jones, M.C., Jones, B.M., and Walter Anthony, K., 2012, Characterizing post-drainage succession in Thermokarst Lake Basins on the Seward Peninsula, Alaska with TerraSAR-X Backscatter and Landsat-based NDVI data: Remote Sensing, v. 4, p. 3741-3765, https://doi.org/10.3390/rs4123741.","productDescription":"25 p. ","startPage":"3741","endPage":"3765","ipdsId":"IP-041633","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":474246,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs4123741","text":"Publisher Index Page"},{"id":342501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Seward Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -160.4443359375,\n 66.46066349658045\n ],\n [\n -161.806640625,\n 66.23145747862573\n ],\n [\n -162.3779296875,\n 66.12496236487968\n ],\n [\n -163.30078125,\n 66.16051056018838\n ],\n [\n -163.564453125,\n 66.42553717157787\n ],\n [\n -163.564453125,\n 66.65297740055279\n ],\n [\n -164.35546875,\n 66.75724984139227\n ],\n [\n -165.9375,\n 66.58321725728175\n ],\n [\n -167.2119140625,\n 66.31986144668052\n ],\n [\n -168.00292968749997,\n 66.01801815922045\n ],\n [\n -168.7060546875,\n 65.4034447883078\n ],\n [\n -167.6953125,\n 64.4348920430406\n ],\n [\n -165.9814453125,\n 64.01449619484472\n ],\n [\n -163.30078125,\n 63.93737246791484\n ],\n [\n -162.20214843749997,\n 64.35893097894458\n ],\n [\n -161.3232421875,\n 64.60503753178527\n ],\n [\n -161.0595703125,\n 64.77412531292873\n ],\n [\n -160.4443359375,\n 65.164578884019\n ],\n [\n -160.26855468749997,\n 65.56754970214311\n ],\n [\n -160.048828125,\n 65.92855383515203\n ],\n [\n -160.4443359375,\n 66.46066349658045\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2012-11-27","publicationStatus":"PW","scienceBaseUri":"59424b3de4b0764e6c65dc75","contributors":{"authors":[{"text":"Regmi, Prajna","contributorId":192910,"corporation":false,"usgs":false,"family":"Regmi","given":"Prajna","email":"","affiliations":[],"preferred":false,"id":698124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":698123,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Miriam C. 0000-0002-6650-7619 miriamjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":4056,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"miriamjones@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":698122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":698121,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walter Anthony, Katey","contributorId":192911,"corporation":false,"usgs":false,"family":"Walter Anthony","given":"Katey","affiliations":[],"preferred":false,"id":698125,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70041260,"text":"70041260 - 2012 - Toxicity of waters from the St. Lawrence River at Massena Area-of-Concern to the plankton species Selenastrum capricornutum and Ceriodaphnia dubia","interactions":[],"lastModifiedDate":"2012-12-01T16:55:20","indexId":"70041260","displayToPublicDate":"2012-11-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Toxicity of waters from the St. Lawrence River at Massena Area-of-Concern to the plankton species Selenastrum capricornutum and Ceriodaphnia dubia","docAbstract":"In 1972, the US and Canada committed to restore the chemical, physical, and biological integrity of the Great Lakes Ecosystem under the first Great Lakes Water Quality Agreement. During subsequent amendments, part of the St. Lawrence River at Massena NY, and segments of three tributaries, were designated as one Area of Concern (AOC) due to various beneficial use impairments (BUIs). Plankton beneficial use was designated impaired within this AOC because phytoplankton and zooplankton population data were unavailable or needed “further assessment”. Contaminated sediments from industrial waste disposal have been largely remediated, thus, the plankton BUI may currently be obsolete. The St. Lawrence River at Massena AOC remedial action plan established two criteria which may be used to assess the plankton BUI; the second states that, “in the absence of community structure data, plankton bioassays confirm no toxicity impact in ambient waters”. This study was implemented during 2011 to determine whether this criterion was achieved. Acute toxicity and chronic toxicity of local waters were quantified seasonally using standardized bioassays with green alga Selenastrum capricornutum and water flea Ceriodaphnia dubia to test the hypothesis that waters from sites within the AOC were no more toxic than were waters from adjacent reference sites. The results of univariate and multivariate analyses confirm that ambient waters from most AOC sites (and seasons) were not toxic to both species. Assuming both test species represent natural plankton assemblages, the quality of surface waters throughout most of this AOC should not seriously impair the health of resident plankton communities.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"International Association for Great Lakes Research","publisherLocation":"Ann Arbor, MI","doi":"10.1016/j.jglr.2012.09.008","usgsCitation":"Baldigo, B.P., Duffy, B.T., Nally, C.J., and David, A.M., 2012, Toxicity of waters from the St. Lawrence River at Massena Area-of-Concern to the plankton species Selenastrum capricornutum and Ceriodaphnia dubia: Journal of Great Lakes Research, v. 38, no. 4, p. 812-820, https://doi.org/10.1016/j.jglr.2012.09.008.","productDescription":"9 p.","startPage":"812","endPage":"820","ipdsId":"IP-035122","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":263543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263542,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2012.09.008"}],"country":"Canada;United States","state":"New York","city":"Massena","otherGeospatial":"Great Lakes;St. Lawrence River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.0,42.0 ], [ -80.0,47.0 ], [ -70.0,47.0 ], [ -70.0,42.0 ], [ -80.0,42.0 ] ] ] } } ] }","volume":"38","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e553e3e4b0a4aa5bb0221f","contributors":{"authors":[{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duffy, Brian T.","contributorId":6352,"corporation":false,"usgs":true,"family":"Duffy","given":"Brian","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":469473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nally, Christopher J.","contributorId":24254,"corporation":false,"usgs":true,"family":"Nally","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":469474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"David, Anthony M.","contributorId":36032,"corporation":false,"usgs":true,"family":"David","given":"Anthony","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":469475,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70041141,"text":"ofr20121245 - 2012 - Linking physical monitoring to coho and Chinook salmon populations in the Redwood Creek Watershed, California—Summary of May 3–4, 2012 Workshop","interactions":[],"lastModifiedDate":"2018-03-21T14:40:08","indexId":"ofr20121245","displayToPublicDate":"2012-11-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1245","title":"Linking physical monitoring to coho and Chinook salmon populations in the Redwood Creek Watershed, California—Summary of May 3–4, 2012 Workshop","docAbstract":"On Thursday, May 3, 2012, a science workshop was held at the Redwood National and State Parks (RNSP) office in Arcata, California, with researchers and resource managers working in RNSP to share data and expert opinions concerning salmon populations and habitat in the Redwood Creek watershed. The focus of the workshop was to discuss how best to synthesize physical and biological data related to the freshwater and estuarine phases of salmon life cycles in order to increase the understanding of constraints on salmon populations. The workshop was hosted by the U.S. Geological Survey (USGS) Status and Trends (S&T) Program National Park Monitoring Project (http://www.fort.usgs.gov/brdscience/ParkMonitoring.htm), which supports USGS research on priority topics (themes) identified by the National Park Service (NPS) Inventory and Monitoring Program (I&M) and S&T. The NPS has organized more than 270 parks with significant natural resources into 32 Inventory and Monitoring (I&M) Networks (http://science.nature.nps.gov/im/networks.cfm) that share funding and core professional staff to monitor the status and long-term trends of selected natural resources (http://science.nature.nps.gov/im/monitor). All 32 networks have completed vital signs monitoring plans (available at http://science.nature.nps.gov/im/monitor/MonitoringPlans.cfm), containing background information on the important resources of each park, conceptual models behind the selection of vital signs for monitoring the condition of natural resources, and the selection of high priority vital signs for monitoring. Vital signs are particular physical, chemical, and biological elements and processes of park ecosystems that represent the overall health or condition of the park, known or hypothesized effects of stressors, or elements that have important human values (Fancy and others, 2009). Beginning in 2009, the I&M program funded projects to analyze and synthesize the biotic and abiotic data generated by vital signs monitoring and previous in-park natural resource monitoring and inventories to provide useful information, models, and tools to park managers for addressing resource management issues. The workshop described in this report is an element of the project funded by USGS NPS-I&M program to conduct a synthesis of salmon-related datasets in the Klamath (KLMN) and San Francisco Bay Area (SFAN) networks of national parks. The synthesis focused on four park units: Redwood National Park (KLMN), Point Reyes National Seashore, Muir Woods National Monument, and Golden Gate National Recreation Area (SFAN).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121245","usgsCitation":"Madej, M.A., Torregrosa, A.A., and Woodward, A., 2012, Linking physical monitoring to coho and Chinook salmon populations in the Redwood Creek Watershed, California—Summary of May 3–4, 2012 Workshop: U.S. Geological Survey Open-File Report 2012-1245, iv, 24 p., https://doi.org/10.3133/ofr20121245.","productDescription":"iv, 24 p.","numberOfPages":"32","additionalOnlineFiles":"N","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":263490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1245.jpg"},{"id":263488,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1245/"},{"id":263489,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1245/pdf/ofr20121245.pdf"}],"country":"United States","state":"California","city":"Arcata;Orick","otherGeospatial":"Olema Creek;Redwood National And State Parks","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.16,41.0 ], [ -124.16,41.84 ], [ -123.85,41.84 ], [ -123.85,41.0 ], [ -124.16,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50df8f40e4b0dfbe79e6d863","contributors":{"authors":[{"text":"Madej, Mary Ann 0000-0003-2831-3773 mary_ann_madej@usgs.gov","orcid":"https://orcid.org/0000-0003-2831-3773","contributorId":40304,"corporation":false,"usgs":true,"family":"Madej","given":"Mary","email":"mary_ann_madej@usgs.gov","middleInitial":"Ann","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":469447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torregrosa, Alicia A. 0000-0001-7361-2241 atorregrosa@usgs.gov","orcid":"https://orcid.org/0000-0001-7361-2241","contributorId":3471,"corporation":false,"usgs":true,"family":"Torregrosa","given":"Alicia","email":"atorregrosa@usgs.gov","middleInitial":"A.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":469446,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodward, Andrea 0000-0003-0604-9115 awoodward@usgs.gov","orcid":"https://orcid.org/0000-0003-0604-9115","contributorId":3028,"corporation":false,"usgs":true,"family":"Woodward","given":"Andrea","email":"awoodward@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":469445,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041100,"text":"ofr20121230 - 2012 - Soil data for a collapse-scar bog chronosequence in Koyukuk Flats National Wildlife Refuge, Alaska, 2008","interactions":[],"lastModifiedDate":"2012-11-29T10:08:25","indexId":"ofr20121230","displayToPublicDate":"2012-11-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1230","title":"Soil data for a collapse-scar bog chronosequence in Koyukuk Flats National Wildlife Refuge, Alaska, 2008","docAbstract":"Peatlands in the northern permafrost region store large amounts of organic carbon, most of which is currently stored in frozen peat deposits. Recent warming at high-latitudes has accelerated permafrost thaw in peatlands, which will likely result in the loss of soil organic carbon from previously frozen peat deposits to the atmosphere. Here, we report soil organic carbon inventories, soil physical data, and field descriptions from a collapse-scar bog chronosequence located in a peatland ecosystem at Koyukuk Flats National Wildlife Refuge in Alaska.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121230","usgsCitation":"O’Donnell, J., Harden, J.W., Manies, K.L., and Jorgenson, M., 2012, Soil data for a collapse-scar bog chronosequence in Koyukuk Flats National Wildlife Refuge, Alaska, 2008: U.S. Geological Survey Open-File Report 2012-1230, iii, 11 p., https://doi.org/10.3133/ofr20121230.","productDescription":"iii, 11 p.","numberOfPages":"14","onlineOnly":"Y","costCenters":[{"id":434,"text":"National Research Program","active":false,"usgs":true}],"links":[{"id":263470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1230.gif"},{"id":263468,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1230/"},{"id":263469,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1230/OF12-1230.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"Koyukuk Flats National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.997477,64.715896 ], [ -156.997477,64.769533 ], [ -156.724214,64.769533 ], [ -156.724214,64.715896 ], [ -156.997477,64.715896 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4ca0ee4b0e8fec6ce1893","contributors":{"authors":[{"text":"O’Donnell, Jonathan A.","contributorId":6347,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Jonathan A.","affiliations":[],"preferred":false,"id":469433,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":469431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Manies, Kristen L. 0000-0003-4941-9657 kmanies@usgs.gov","orcid":"https://orcid.org/0000-0003-4941-9657","contributorId":2136,"corporation":false,"usgs":true,"family":"Manies","given":"Kristen","email":"kmanies@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":469432,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jorgenson, M. Torre","contributorId":40486,"corporation":false,"usgs":true,"family":"Jorgenson","given":"M. Torre","affiliations":[],"preferred":false,"id":469434,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70041128,"text":"ofr20121227 - 2012 - Hydrostratigraphic interpretation of test-hole and surface geophysical data, Elkhorn and Loup River Basins, Nebraska, 2008 to 2011","interactions":[],"lastModifiedDate":"2012-11-29T14:36:20","indexId":"ofr20121227","displayToPublicDate":"2012-11-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1227","title":"Hydrostratigraphic interpretation of test-hole and surface geophysical data, Elkhorn and Loup River Basins, Nebraska, 2008 to 2011","docAbstract":"The Elkhorn-Loup Model (ELM) was begun in 2006 to understand the effect of various groundwater-management scenarios on surface-water resources. During phase one of the ELM study, a lack of subsurface geological information was identified as a data gap. Test holes drilled to the base of the aquifer in the ELM study area are spaced as much as 25 miles apart, especially in areas of the western Sand Hills. Given the variable character of the hydrostratigraphic units that compose the High Plains aquifer system, substantial variation in aquifer thickness and characteristics can exist between test holes. To improve the hydrogeologic understanding of the ELM study area, the U.S. Geological Survey, in cooperation with the Nebraska Department of Natural Resources, multiple Natural Resources Districts participating in the ELM study, and the University of Nebraska-Lincoln Conservation and Survey Division, described the subsurface lithology at six test holes drilled in 2010 and concurrently collected borehole geophysical data to identify the base of the High Plains aquifer system. A total of 124 time-domain electromagnetic (TDEM) soundings of resistivity were collected at and between selected test-hole locations during 2008-11 as a quick, non-invasive means of identifying the base of the High Plains aquifer system. Test-hole drilling and geophysical logging indicated the base-of-aquifer elevation was less variable in the central ELM area than in previously reported results from the western part of the ELM study area, where deeper paleochannels were eroded into the Brule Formation. In total, more than 435 test holes were examined and compared with the modeled-TDEM soundings. Even where present, individual stratigraphic units could not always be identified in modeled-TDEM sounding results if sufficient resistivity contrast was not evident; however, in general, the base of aquifer [top of the aquifer confining unit (ACU)] is one of the best-resolved results from the TDEM-based models, and estimates of the base-of-aquifer elevation are in good accordance with those from existing test-hole data. Differences between ACU elevations based on modeled-TDEM and test-hole data ranged from 2 to 113 feet (0.6 to 34 meters). The modeled resistivity results reflect the eastward thinning of Miocene-age and older stratigraphic units, and generally allowed confident identification of the accompanying change in the stratigraphic unit forming the ACU. The differences in elevation of the top of the Ogallala, estimated on the basis of the modeled-TDEM resistivity, and the test-hole data ranged from 11 to 251 feet (3.4 to 77 meters), with two-thirds of model results being within 60 feet of the test-hole contact elevation. The modeled-TDEM soundings also provided information regarding the distribution of Plio-Pleistocene gravel deposits, which had an average thickness of 100 feet (30 meters) in the study area; however, in many cases the contact between the Plio-Pleistocene deposits and the overlying Quaternary deposits cannot be reliably distinguished using TDEM soundings alone because of insufficient thickness or resistivity contrast.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121227","collaboration":"Prepared in cooperation with the Nebraska Department of Natural Resources; and the Upper Elkhorn, Lower Elkhorn, Upper Loup, Lower Loup, Middle Niobrara, Lower Niobrara, Lewis and Clark, and Lower Platte North Natural Resources Districts; and the University of Nebraska-Lincoln Conservation and Survey Division","usgsCitation":"Hobza, C.M., Bedrosian, P.A., and Bloss, B., 2012, Hydrostratigraphic interpretation of test-hole and surface geophysical data, Elkhorn and Loup River Basins, Nebraska, 2008 to 2011: U.S. Geological Survey Open-File Report 2012-1227, Report: x, 95 p.; Supplemental Data, https://doi.org/10.3133/ofr20121227.","productDescription":"Report: x, 95 p.; Supplemental Data","numberOfPages":"110","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-037355","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":263482,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1227.gif"},{"id":263481,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1227/downloads/Supplemental_Data.xlsx"},{"id":263478,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1227/"},{"id":263479,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1227/of2012-1227.pdf"}],"scale":"100000","projection":"Lambert Conformal Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Nebraska","otherGeospatial":"Elkhorn And Loup River Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -102.5,40.0 ], [ -102.5,43.0 ], [ -97.0,43.0 ], [ -97.0,40.0 ], [ -102.5,40.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50df06b5e4b0dfbe79e687ab","contributors":{"authors":[{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":469442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bloss, Benjamin R.","contributorId":19446,"corporation":false,"usgs":true,"family":"Bloss","given":"Benjamin R.","affiliations":[],"preferred":false,"id":469444,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041041,"text":"70041041 - 2012 - Peat accumulation in drained thermokarst lake basins in continuous, ice-rich permafrost, northern Seward Peninsula, Alaska","interactions":[],"lastModifiedDate":"2013-02-23T22:15:04","indexId":"70041041","displayToPublicDate":"2012-11-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Peat accumulation in drained thermokarst lake basins in continuous, ice-rich permafrost, northern Seward Peninsula, Alaska","docAbstract":"Thermokarst lakes and peat-accumulating drained lake basins cover a substantial portion of Arctic lowland landscapes, yet the role of thermokarst lake drainage and ensuing peat formation in landscape-scale carbon (C) budgets remains understudied. Here we use measurements of terrestrial peat thickness, bulk density, organic matter content, and basal radiocarbon age from permafrost cores, soil pits, and exposures in vegetated, drained lake basins to characterize regional lake drainage chronology, C accumulation rates, and the role of thermokarst-lake cycling in carbon dynamics throughout the Holocene on the northern Seward Peninsula, Alaska. Most detectable lake drainage events occurred within the last 4,000 years with the highest drainage frequency during the medieval climate anomaly. Peat accumulation rates were highest in young (50–500 years) drained lake basins (35.2 g C m−2 yr−1) and decreased exponentially with time since drainage to 9 g C m−2 yr−1 in the oldest basins. Spatial analyses of terrestrial peat depth, basal peat radiocarbon ages, basin geomorphology, and satellite-derived land surface properties (Normalized Difference Vegetation Index (NDVI); Minimum Noise Fraction (MNF)) from Landsat satellite data revealed significant relationships between peat thickness and mean basin NDVI or MNF. By upscaling observed relationships, we infer that drained thermokarst lake basins, covering 391 km2 (76%) of the 515 km2 study region, store 6.4–6.6 Tg organic C in drained lake basin terrestrial peat. Peat accumulation in drained lake basins likely serves to offset greenhouse gas release from thermokarst-impacted landscapes and should be incorporated in landscape-scale C budgets.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research G: Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2011JG001766","usgsCitation":"Jones, M.C., Grosse, G., Jones, B.M., and Anthony, K.W., 2012, Peat accumulation in drained thermokarst lake basins in continuous, ice-rich permafrost, northern Seward Peninsula, Alaska: Journal of Geophysical Research G: Biogeosciences, v. 117, https://doi.org/10.1029/2011JG001766.","productDescription":"16 p.","startPage":"G00M07","additionalOnlineFiles":"N","ipdsId":"IP-035962","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":263483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263480,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2011JG001766"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.45,51.21 ], [ 172.45,71.39 ], [ -130.0,71.39 ], [ -130.0,51.21 ], [ 172.45,51.21 ] ] ] } } ] }","volume":"117","noUsgsAuthors":false,"publicationDate":"2012-04-07","publicationStatus":"PW","scienceBaseUri":"50e0f56ce4b0fec3206f1c76","contributors":{"authors":[{"text":"Jones, Miriam C. 0000-0002-6650-7619 miriamjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6650-7619","contributorId":4056,"corporation":false,"usgs":true,"family":"Jones","given":"Miriam","email":"miriamjones@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":469233,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":469235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":469232,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Anthony, Katey Walter","contributorId":77441,"corporation":false,"usgs":true,"family":"Anthony","given":"Katey","email":"","middleInitial":"Walter","affiliations":[],"preferred":false,"id":469234,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70040995,"text":"ofr20121236 - 2012 - Temporal and spatial trends of chloride and sodium in groundwater in New Hampshire, 1960–2011","interactions":[],"lastModifiedDate":"2016-08-10T15:54:18","indexId":"ofr20121236","displayToPublicDate":"2012-11-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1236","title":"Temporal and spatial trends of chloride and sodium in groundwater in New Hampshire, 1960–2011","docAbstract":"Data on concentrations of chloride and sodium in groundwater in New Hampshire were assembled from various State and Federal agencies and organized into a database. This report provides documentation of many assumptions and limitations of disparate data that were collected to meet wide-ranging objectives and investigates temporal and spatial trends of the data. Data summaries presented in this report and analyses performed for this study needed to take into account the 27 percent of chloride and 5 percent of sodium data that were censored (less than a reporting limit) at multiple reporting limits that systematically decreased over time. Throughout New Hampshire, median concentrations of chloride were significantly greater during 2000-2011 than in every decade since the 1970s, and median concentrations of sodium were significantly greater during 2000-2011 than during the 1990s. Results of summary statistics showed that the 50th, 75th, and 90th percentiles of the median concentrations of chloride and sodium by source (well) from Rockingham and Strafford counties were the highest in the State; and the 75th and 90th percentiles from Carroll, Coos, and Grafton counties were the lowest. Large increases in median concentrations of chloride and sodium for individual wells after 1995 compared with concentrations for years before were found in parts of Belknap and Rockingham counties and in small clusters within Carroll, Hillsborough, and Merrimack counties.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121236","collaboration":"Prepared in cooperation with the New Hampshire Department of Environmental Services","usgsCitation":"Medalie, L., 2012, Temporal and spatial trends of chloride and sodium in groundwater in New Hampshire, 1960–2011: U.S. Geological Survey Open-File Report 2012-1236, v, 25 p., https://doi.org/10.3133/ofr20121236.","productDescription":"v, 25 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":263435,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1236/"},{"id":263436,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1236/pdf/ofr2012-1236_report_508.pdf","text":"Report","size":"1.73 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Hampshire\",\"nation\":\"USA \"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4f4a3e4b0e8fec6ce763c","contributors":{"authors":[{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469193,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70041019,"text":"ofr20121111 - 2012 - Preliminary catalog of the sedimentary basins of the United States","interactions":[],"lastModifiedDate":"2012-11-28T12:07:05","indexId":"ofr20121111","displayToPublicDate":"2012-11-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1111","title":"Preliminary catalog of the sedimentary basins of the United States","docAbstract":"One hundred forty-four sedimentary basins (or groups of basins) in the United States (both onshore and offshore) are identified, located, and briefly described as part of a Geographic Information System (GIS) data base in support of the Geologic Carbon Dioxide Sequestration National Assessment Project (Brennan and others, 2010). This catalog of basins is designed to provide a check list and basic geologic framework for compiling more detailed geologic and reservoir engineering data for this project and other future investigations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121111","usgsCitation":"Coleman, J.L., and Cahan, S.M., 2012, Preliminary catalog of the sedimentary basins of the United States: U.S. Geological Survey Open-File Report 2012-1111, Report: iv, 27 p.; 4 Figures: 17 x 11 inches; 1 Table; Sedimentary Basins Database; Metadata, https://doi.org/10.3133/ofr20121111.","productDescription":"Report: iv, 27 p.; 4 Figures: 17 x 11 inches; 1 Table; Sedimentary Basins Database; Metadata","numberOfPages":"31","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":263451,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1111/pdf/Figure_2_MESOZOIC.pdf"},{"id":263452,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1111/pdf/Figure_3_PALEOZOIC.pdf"},{"id":263448,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1111/"},{"id":263449,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1111/pdf/ofr2012-1111.pdf"},{"id":263450,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1111/pdf/Figure_1_CENOZOIC.pdf"},{"id":263453,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1111/pdf/Figure_4_NEOPROTEROZOIC.pdf"},{"id":263454,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2012/1111/pdf/table1.pdf"},{"id":263455,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2012/1111/data/Sedimentary_Basins.zip"},{"id":263456,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2012/1111/Sedimentary_Basins_of_the_United_States.html"},{"id":263457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1111.jpg"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173.0,16.916667 ], [ 173.0,71.833333 ], [ -66.95,71.833333 ], [ -66.95,16.916667 ], [ 173.0,16.916667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e189d0e4b0ff1e7c578d19","contributors":{"authors":[{"text":"Coleman, James L. Jr. 0000-0002-5232-5849 jlcoleman@usgs.gov","orcid":"https://orcid.org/0000-0002-5232-5849","contributorId":549,"corporation":false,"usgs":true,"family":"Coleman","given":"James","suffix":"Jr.","email":"jlcoleman@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":469213,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cahan, Steven M. 0000-0002-4776-3668 scahan@usgs.gov","orcid":"https://orcid.org/0000-0002-4776-3668","contributorId":4529,"corporation":false,"usgs":true,"family":"Cahan","given":"Steven","email":"scahan@usgs.gov","middleInitial":"M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":469214,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70040996,"text":"fs20123112 - 2012 - Slope-Area Computation Program Graphical User Interface 1.0—A Preprocessing and Postprocessing Tool for Estimating Peak Flood Discharge Using the Slope-Area Method","interactions":[],"lastModifiedDate":"2012-11-28T10:18:37","indexId":"fs20123112","displayToPublicDate":"2012-11-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-3112","title":"Slope-Area Computation Program Graphical User Interface 1.0—A Preprocessing and Postprocessing Tool for Estimating Peak Flood Discharge Using the Slope-Area Method","docAbstract":"The slope-area method is a technique for estimating the peak discharge of a flood after the water has receded (Dalrymple and Benson, 1967). This type of discharge estimate is called an “indirect measurement” because it relies on evidence left behind by the flood, such as high-water marks (HWMs) on trees or buildings. These indicators of flood stage are combined with measurements of the cross-sectional geometry of the stream, estimates of channel roughness, and a mathematical model that balances the total energy of the flow between cross sections. This is in contrast to a “direct” measurement of discharge during the flood where cross-sectional area is measured and a current meter or acoustic equipment is used to measure the water velocity. When a direct discharge measurement cannot be made at a gage during high flows because of logistics or safety reasons, an indirect measurement of a peak discharge is useful for defining the high-flow section of the stage-discharge relation (rating curve) at the stream gage, resulting in more accurate computation of high flows. The Slope-Area Computation program (SAC; Fulford, 1994) is an implementation of the slope-area method that computes a peak-discharge estimate from inputs of water-surface slope (from surveyed HWMs), channel geometry, and estimated channel roughness. SAC is a command line program written in Fortran that reads input data from a formatted text file and prints results to another formatted text file. Preparing the input file can be time-consuming and prone to errors. This document describes the SAC graphical user interface (GUI), a crossplatform “wrapper” application that prepares the SAC input file, executes the program, and helps the user interpret the output. The SAC GUI is an update and enhancement of the slope-area method (SAM; Hortness, 2004; Berenbrock, 1996), an earlier spreadsheet tool used to aid field personnel in the completion of a slope-area measurement. The SAC GUI reads survey data, develops a plan-view plot, water-surface profile, cross-section plots, and develops the SAC input file. The SAC GUI also develops HEC-2 files that can be imported into HEC–RAS.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123112","usgsCitation":"Bradley, D.N., 2012, Slope-Area Computation Program Graphical User Interface 1.0—A Preprocessing and Postprocessing Tool for Estimating Peak Flood Discharge Using the Slope-Area Method: U.S. Geological Survey Fact Sheet 2012-3112, 4 p., https://doi.org/10.3133/fs20123112.","productDescription":"4 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":306,"text":"Geology Research and Information","active":false,"usgs":true}],"links":[{"id":263443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3112.gif"},{"id":263442,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3112/fs2012-3112.pdf"},{"id":263441,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3112/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4c921e4b0e8fec6ce1663","contributors":{"authors":[{"text":"Bradley, D. Nathan","contributorId":79776,"corporation":false,"usgs":true,"family":"Bradley","given":"D.","email":"","middleInitial":"Nathan","affiliations":[],"preferred":false,"id":469194,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048348,"text":"70048348 - 2012 - Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters","interactions":[],"lastModifiedDate":"2016-11-30T13:30:53","indexId":"70048348","displayToPublicDate":"2012-11-27T11:41:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters","docAbstract":"Coastal and estuarine waters are the site of intense anthropogenic influence with concomitant use for recreation and seafood harvesting. Therefore, coastal and estuarine water quality has a direct impact on human health. In eastern North Carolina (NC) there are over 240 recreational and 1025 shellfish harvesting water quality monitoring sites that are regularly assessed. Because of the large number of sites, sampling frequency is often only on a weekly basis. This frequency, along with an 18–24 h incubation time for fecal indicator bacteria (FIB) enumeration via culture-based methods, reduces the efficiency of the public notification process. In states like NC where beach monitoring resources are limited but historical data are plentiful, predictive models may offer an improvement for monitoring and notification by providing real-time FIB estimates. In this study, water samples were collected during 12 dry (n = 88) and 13 wet (n = 66) weather events at up to 10 sites. Statistical predictive models for Escherichiacoli (EC), enterococci (ENT), and members of the Bacteroidales group were created and subsequently validated. Our results showed that models for EC and ENT (adjusted R2 were 0.61 and 0.64, respectively) incorporated a range of antecedent rainfall, climate, and environmental variables. The most important variables for EC and ENT models were 5-day antecedent rainfall, dissolved oxygen, and salinity. These models successfully predicted FIB levels over a wide range of conditions with a 3% (EC model) and 9% (ENT model) overall error rate for recreational threshold values and a 0% (EC model) overall error rate for shellfish threshold values. Though modeling of members of the Bacteroidales group had less predictive ability (adjusted R2 were 0.56 and 0.53 for fecal Bacteroides spp. and human Bacteroides spp., respectively), the modeling approach and testing provided information on Bacteroidales ecology. This is the first example of a set of successful statistical predictive models appropriate for assessment of both recreational and shellfish harvesting water quality in estuarine waters.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2012.07.050","usgsCitation":"Gonzalez, R., Conn, K., Crosswell, J., and Noble, R., 2012, Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters: Water Research, v. 46, no. 18, p. 5871-5882, https://doi.org/10.1016/j.watres.2012.07.050.","productDescription":"12 p.","startPage":"5871","endPage":"5882","ipdsId":"IP-036574","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":278005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278004,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.watres.2012.07.050"}],"country":"United States","state":"North Carolina","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.709756,34.769892 ], [ -76.709756,34.78618 ], [ -76.669006,34.78618 ], [ -76.669006,34.769892 ], [ -76.709756,34.769892 ] ] ] } } ] }","volume":"46","issue":"18","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"524162e2e4b0ec672f073ad1","contributors":{"authors":[{"text":"Gonzalez, Raul","contributorId":17131,"corporation":false,"usgs":true,"family":"Gonzalez","given":"Raul","email":"","affiliations":[],"preferred":false,"id":484361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, Kathleen E. 0000-0002-2334-6536 kconn@usgs.gov","orcid":"https://orcid.org/0000-0002-2334-6536","contributorId":3923,"corporation":false,"usgs":true,"family":"Conn","given":"Kathleen E.","email":"kconn@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crosswell, Joey","contributorId":75437,"corporation":false,"usgs":true,"family":"Crosswell","given":"Joey","affiliations":[],"preferred":false,"id":484362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noble, Rachel","contributorId":82212,"corporation":false,"usgs":true,"family":"Noble","given":"Rachel","affiliations":[],"preferred":false,"id":484363,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70038918,"text":"70038918 - 2012 - Effect of survey design and catch rate estimation on total catch estimates in Chinook salmon fisheries","interactions":[],"lastModifiedDate":"2012-11-27T09:04:26","indexId":"70038918","displayToPublicDate":"2012-11-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Effect of survey design and catch rate estimation on total catch estimates in Chinook salmon fisheries","docAbstract":"Roving–roving and roving–access creel surveys are the primary techniques used to obtain information on harvest of Chinook salmon Oncorhynchus tshawytscha in Idaho sport fisheries. Once interviews are conducted using roving–roving or roving–access survey designs, mean catch rate can be estimated with the ratio-of-means (ROM) estimator, the mean-of-ratios (MOR) estimator, or the MOR estimator with exclusion of short-duration (≤0.5 h) trips. Our objective was to examine the relative bias and precision of total catch estimates obtained from use of the two survey designs and three catch rate estimators for Idaho Chinook salmon fisheries. Information on angling populations was obtained by direct visual observation of portions of Chinook salmon fisheries in three Idaho river systems over an 18-d period. Based on data from the angling populations, Monte Carlo simulations were performed to evaluate the properties of the catch rate estimators and survey designs. Among the three estimators, the ROM estimator provided the most accurate and precise estimates of mean catch rate and total catch for both roving–roving and roving–access surveys. On average, the root mean square error of simulated total catch estimates was 1.42 times greater and relative bias was 160.13 times greater for roving–roving surveys than for roving–access surveys. Length-of-stay bias and nonstationary catch rates in roving–roving surveys both appeared to affect catch rate and total catch estimates. Our results suggest that use of the ROM estimator in combination with an estimate of angler effort provided the least biased and most precise estimates of total catch for both survey designs. However, roving–access surveys were more accurate than roving–roving surveys for Chinook salmon fisheries in Idaho.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"North American Journal of Fisheries Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/02755947.2012.716017","usgsCitation":"McCormick, J.L., Quist, M.C., and Schill, D.J., 2012, Effect of survey design and catch rate estimation on total catch estimates in Chinook salmon fisheries: North American Journal of Fisheries Management, v. 32, no. 6, p. 1090-1101, https://doi.org/10.1080/02755947.2012.716017.","productDescription":"12 p.","startPage":"1090","endPage":"1101","additionalOnlineFiles":"N","ipdsId":"IP-037567","costCenters":[{"id":342,"text":"Idaho Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":263401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263400,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02755947.2012.716017"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.0,42.0 ], [ -117.0,49.0 ], [ -111.0,49.0 ], [ -111.0,42.0 ], [ -117.0,42.0 ] ] ] } } ] }","volume":"32","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-10-31","publicationStatus":"PW","scienceBaseUri":"50db2804e4b0612706008dd2","contributors":{"authors":[{"text":"McCormick, Joshua L.","contributorId":105193,"corporation":false,"usgs":true,"family":"McCormick","given":"Joshua","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":465237,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. mquist@usgs.gov","contributorId":4042,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":350,"text":"Iowa Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":465235,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schill, Daniel J.","contributorId":66562,"corporation":false,"usgs":true,"family":"Schill","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":465236,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70040902,"text":"sir20125249 - 2012 - Hydrogeology and water quality of the Floridan aquifer system and effect of Lower Floridan aquifer pumping on the Upper Floridan aquifer, Pooler, Chatham County, Georgia, 2011–2012","interactions":[],"lastModifiedDate":"2021-03-24T17:17:41.465185","indexId":"sir20125249","displayToPublicDate":"2012-11-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5249","title":"Hydrogeology and water quality of the Floridan aquifer system and effect of Lower Floridan aquifer pumping on the Upper Floridan aquifer, Pooler, Chatham County, Georgia, 2011–2012","docAbstract":"Two test wells were completed in Pooler, Georgia, in 2011 to investigate the potential of using the Lower Floridan aquifer as a source of water for municipal use. One well was completed in the Lower Floridan aquifer at a depth of 1,120 feet (ft) below land surface; the other well was completed in the Upper Floridan aquifer at a depth of 486 ft below land surface. At the Pooler test site, the U.S. Geological Survey performed flowmeter surveys, packer-isolated slug tests within the Lower Floridan confining unit, slug tests of the entire Floridan aquifer system, and aquifer tests of the Upper and Lower Floridan aquifers. Drill cuttings, geophysical logs, and borehole flowmeter surveys indicate that the Upper Floridan aquifer extends 333 –515 ft below land surface, the Lower Floridan confining unit extends 515–702 ft below land surface, and the Lower Floridan aquifer extends 702–1,040 ft below land surface. Flowmeter surveys indicate that the Upper Floridan aquifer contains two water-bearing zones at depth intervals of 339 –350 and 375–515 ft; the Lower Floridan confining unit contains one zone at a depth interval of 550–620 ft; and the Lower Floridan aquifer contains five zones at depth intervals of 702–745, 745–925, 925–984, 984–1,015, and 1,015–1,040 ft. Flowmeter testing of the test borehole open to the entire Floridan aquifer system indicated that the Upper Floridan aquifer contributed 92.4 percent of the total flow rate of 708 gallons per minute; the Lower Floridan confining unit contributed 3.0 percent; and the Lower Floridan aquifer contributed 4.6 percent. Horizontal hydraulic conductivity of the Lower Floridan confining unit derived from slug tests within three packer-isolated intervals ranged from 0.5 to 10 feet per day (ft/d). Aquifer-test analyses yielded values of transmissivity for the Upper Floridan aquifer, Lower Floridan confining unit, and the Lower Floridan aquifer of 46,000, 700, and 4,000 feet squared per day (ft2/d), respectively. Horizontal hydraulic conductivity of 4 ft/d for the Lower Floridan confining unit, derived from aquifer-test analyses, is near the midrange for values derived from packer-isolated slug tests. The transmissivity of the entire Floridan aquifer system derived from aquifer-test analyses totals about 51,000 ft2/d, similar to the value of 58,000 ft2/d derived from open slug tests on the entire Floridan aquifer system. Water-level data for each aquifer test were filtered for external influences such as barometric pressure, earth-tide effects, and long-term trends to enable detection of small (less than 1 foot) water-level responses to aquifer-test pumping. During the 72-hour aquifer test of pumping the Lower Floridan aquifer, a drawdown response of 51.7 ft was observed in the Lower Floridan pumped well and a drawdown response of 0.9 foot was observed in the Upper Floridan observation well located 85 ft from the pumped well.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125249","collaboration":"Prepared in cooperation with the City of Pooler, Georgia","usgsCitation":"Gonthier, G., 2012, Hydrogeology and water quality of the Floridan aquifer system and effect of Lower Floridan aquifer pumping on the Upper Floridan aquifer, Pooler, Chatham County, Georgia, 2011–2012: U.S. Geological Survey Scientific Investigations Report 2012-5249, x, 62 p., https://doi.org/10.3133/sir20125249.","productDescription":"x, 62 p.","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":263411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5249.jpg"},{"id":263410,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5249/pdf/sir2012-5249.pdf"},{"id":263409,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5249/"}],"scale":"2000000","country":"United States","state":"Georgia","county":"Chatham County","city":"Pooler","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.75,31.75 ], [ -81.75,32.25 ], [ -80.75,32.25 ], [ -80.75,31.75 ], [ -81.75,31.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50deeeb0e4b0dfbe79e663f4","contributors":{"authors":[{"text":"Gonthier, Gerard 0000-0003-4078-8579 gonthier@usgs.gov","orcid":"https://orcid.org/0000-0003-4078-8579","contributorId":3141,"corporation":false,"usgs":true,"family":"Gonthier","given":"Gerard ","email":"gonthier@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":469170,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70040911,"text":"70040911 - 2012 - Spatial and temporal trends of freshwater mussel assemblages in the Meramec River Basin, Missouri, USA","interactions":[],"lastModifiedDate":"2017-05-22T14:53:44","indexId":"70040911","displayToPublicDate":"2012-11-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal trends of freshwater mussel assemblages in the Meramec River Basin, Missouri, USA","docAbstract":"The Meramec River basin in east-central Missouri has one of the most diverse unionoid mussel faunas in the central United States with >40 species identified. Data were analyzed from historical surveys to test whether diversity and abundance of mussels in the Meramec River basin (Big, Bourbeuse, and Meramec rivers, representing >400 river miles) decreased between 1978 and 1997. We found that over 20y, species richness and diversity decreased significantly in the Bourbeuse and Meramec rivers but not in the Big River. Most species were found at fewer sites and in lower numbers in 1997 than in 1978. Federally endangered species and Missouri Species of Conservation Concern with the most severe temporal declines were Alasmidonta viridis, Arcidens confragosus, Elliptio crassidens, Epioblasma triquetra, Fusconaia ebena, Lampsilis abrupta, Lampsilis brittsi, and Simpsonaias ambigua. Averaged across all species, mussels were generally being extirpated from historical sampling sites more rapidly than colonization was occurring. An exception was one reach of the Meramec River between river miles 28.4 and 59.5, where mussel abundance and diversity were greater than in other reaches and where colonization of Margaritiferidae, Lampsilini, and Quadrulini exceeded extirpation. The exact reasons mussel diversity and abundance have remained robust in this 30- mile reach is uncertain, but the reach is associated with increased gradients, few long pools, and vertical rock faces, all of which are preferable for mussels. Complete loss of mussel communities at eight sites (16%) with relatively diverse historical assemblages was attributed to physical habitat changes including bank erosion, unstable substrate, and sedimentation. Mussel conservation efforts, including restoring and protecting riparian habitats, limiting the effects of in-stream sand and gravel mining, monitoring and controlling invasive species, and protecting water quality, may be warranted in the Meramec River basin.","language":"English","publisher":"Scientific Journals","doi":"10.3996/052012-JFWM-038","usgsCitation":"Hinck, J.E., McMurray, S., Roberts, A.D., Barnhart, M., Ingersoll, C.G., Wang, N., and Augspurger, T., 2012, Spatial and temporal trends of freshwater mussel assemblages in the Meramec River Basin, Missouri, USA: Journal of Fish and Wildlife Management, v. 3, no. 2, p. 319-331, https://doi.org/10.3996/052012-JFWM-038.","productDescription":"13 p.","startPage":"319","endPage":"331","ipdsId":"IP-035423","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":474255,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/052012-jfwm-038","text":"Publisher Index Page"},{"id":263420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263419,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3996/052012-JFWM-038"}],"country":"United States","state":"Missouri","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.77,36.0 ], [ -95.77,40.61 ], [ -89.1,40.61 ], [ -89.1,36.0 ], [ -95.77,36.0 ] ] ] } } ] }","volume":"3","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4ce19e4b0e8fec6ce2279","contributors":{"authors":[{"text":"Hinck, Jo Ellen 0000-0002-4912-5766","orcid":"https://orcid.org/0000-0002-4912-5766","contributorId":38507,"corporation":false,"usgs":true,"family":"Hinck","given":"Jo","email":"","middleInitial":"Ellen","affiliations":[],"preferred":false,"id":469173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMurray, Stephen E.","contributorId":38687,"corporation":false,"usgs":true,"family":"McMurray","given":"Stephen E.","affiliations":[],"preferred":false,"id":469174,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roberts, Andrew D.","contributorId":52304,"corporation":false,"usgs":true,"family":"Roberts","given":"Andrew","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":469175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, M. Christopher","contributorId":78061,"corporation":false,"usgs":true,"family":"Barnhart","given":"M. Christopher","affiliations":[],"preferred":false,"id":469177,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":469171,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":469172,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Augspurger, Tom","contributorId":63921,"corporation":false,"usgs":true,"family":"Augspurger","given":"Tom","affiliations":[],"preferred":false,"id":469176,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70040977,"text":"sir20125139 - 2012 - Evaluation of volatile organic compound (VOC) blank data and application of study reporting levels to groundwater data collected for the California GAMA Priority Basin Project, May 2004 through September 2010","interactions":[],"lastModifiedDate":"2012-11-27T20:00:08","indexId":"sir20125139","displayToPublicDate":"2012-11-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5139","title":"Evaluation of volatile organic compound (VOC) blank data and application of study reporting levels to groundwater data collected for the California GAMA Priority Basin Project, May 2004 through September 2010","docAbstract":"Volatile organic compounds (VOCs) were analyzed in quality-control samples collected for the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project. From May 2004 through September 2010, a total of 2,026 groundwater samples, 211 field blanks, and 109 source-solution blanks were collected and analyzed for concentrations of 85 VOCs. Results from analyses of these field and source-solution blanks and of 2,411 laboratory instrument blanks during the same time period were used to assess the quality of data for the 2,026 groundwater samples. Eighteen VOCs were detected in field blanks or source-solution blanks: acetone, benzene, bromodichloromethane, 2-butanone, carbon disulfide, chloroform, 1,1-dichloroethene, dichloromethane, ethylbenzene, tetrachloroethene, styrene, tetrahydrofuran, toluene, trichloroethene, trichlorofluoromethane, 1,2,4-trimethylbenzene, m- and p-xylenes, and o-xylene.\n\nThe objective of the evaluation of the VOC-blank data was to determine if study reporting levels (SRLs) were needed for any of the VOCs detected in blanks to ensure the quality of the data from groundwater samples. An SRL is equivalent to a raised reporting level that is used in place of the reporting level used by the analyzing laboratory [long‑term method detection level (LT-MDL) or laboratory reporting level (LRL)] to reduce the probability of reporting false-positive detections. Evaluation of VOC-blank data was done in three stages: (1) identification of a set of representative quality‑control field blanks (QCFBs) to be used for calculation of SRLs and identification of VOCs amenable to the SRL approach, (2) evaluation of potential sources of contamination to blanks and groundwater samples by VOCs detected in field blanks, and (3) selection of appropriate SRLs from among four potential SRLs for VOCs detected in field blanks and application of those SRLs to the groundwater data. An important conclusion from this study is that to ensure the quality of the data from groundwater samples, it was necessary to apply different methods of determining SRLs from field blank data to different VOCs, rather than use the same method for all VOCs.\n\nFour potential SRL values were defined by using three approaches: two values were defined by using a binomial probability method based on one-sided, nonparametric upper confidence limits, one was defined as equal to the maximum concentration detected in the field blanks, and one was defined as equal to the maximum laboratory method detection level used during the period when samples were collected for the project. The differences in detection frequencies and concentrations among different types of blanks (laboratory instrument blanks, source-solution blanks, and field blanks collected with three different sampling equipment configurations) and groundwater samples were used to infer the sources and mechanisms of contamination for each VOC detection in field blanks. Other chemical data for the groundwater samples (oxidation-reduction state, co-occurrence of VOCs, groundwater age) and ancillary information about the well sites (land use, presence of known sources of contamination) were used to evaluate whether the patterns of detections of VOCs in groundwater samples before and after application of potential SRLs were plausible. On this basis, the appropriate SRL was selected for each VOC that was determined to require an SRL.\n\nThe SRLs for ethylbenzene [0.06 microgram per liter (μg/L)], m- and p-xylenes (0.33 μg/L), o-xylene (0.12 μg/L), toluene (0.69 μg/L), and 1,2,4-trimethylbenzene (0.56 μg/L) corresponded to the highest concentrations detected in the QCFBs and were selected because they resulted in the most censoring of groundwater data. Comparisons of hydrocarbon ratios in groundwater samples and blanks and comparisons between detection frequencies of the five hydrocarbons in groundwater samples and different types of blanks suggested three dominant sources of contamination that affected groundwater samples and blanks: (1) ethylbenzene, m- and p-xylenes, o-xylene, and toluene from fuel or exhaust components sorbed onto sampling lines, (2) toluene from vials and the source blank water, and (3) 1,2,4-trimethylbenzene from materials used for collection of samples for radon-222 analysis.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125139","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Fram, M.S., Olsen, L., and Belitz, K., 2012, Evaluation of volatile organic compound (VOC) blank data and application of study reporting levels to groundwater data collected for the California GAMA Priority Basin Project, May 2004 through September 2010: U.S. Geological Survey Scientific Investigations Report 2012-5139, viii, 94 p.; col. ill.; maps (col.), https://doi.org/10.3133/sir20125139.","productDescription":"viii, 94 p.; col. ill.; maps (col.)","startPage":"i","endPage":"94","numberOfPages":"106","additionalOnlineFiles":"N","temporalStart":"2004-05-01","temporalEnd":"2010-09-30","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":263432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5139.jpg"},{"id":263430,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5139/"},{"id":263431,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5139/pdf/sir20125139.pdf"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.01 ], [ -114.13,42.01 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50dca8b1e4b0d55926e3ec23","contributors":{"authors":[{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olsen, Lisa D. ldolsen@usgs.gov","contributorId":2707,"corporation":false,"usgs":true,"family":"Olsen","given":"Lisa D.","email":"ldolsen@usgs.gov","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":469185,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469183,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70040856,"text":"ofr20121249 - 2012 - Assessment of photographs from wildlife monitoring cameras in Drakes Estero, Point Reyes National Seashore, California","interactions":[],"lastModifiedDate":"2018-08-10T16:54:40","indexId":"ofr20121249","displayToPublicDate":"2012-11-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1249","title":"Assessment of photographs from wildlife monitoring cameras in Drakes Estero, Point Reyes National Seashore, California","docAbstract":"Between 2007 and 2010, National Park Service (NPS) staff at the Point Reyes National Seashore, California, collected over 300,000 photographic images of Drakes Estero from remotely operated wildlife monitoring cameras. The purpose of the systems was to obtain photographic data to help understand possible relationships between anthropogenic activities and Pacific harbor seal (Phoca vitulina richardsi) behavior and distribution. \n\nThe value of the NPS photographs for use in assessing the frequency and impacts of seal disturbance and displacement in Drakes Estero has been debated. In September 2011, the NPS determined that the photographs did not provide meaningful information for development of a Draft Environmental Impact Statement (DEIS) for the Drakes Bay Oyster Company Special Use Permit. Limitations of the photographs included lack of study design, poor photographic quality, inadequate field of view, incomplete estuary coverage, camera obstructions, and weather limitations. \n\nThe Marine Mammal Commission (MMC) reviewed the scientific data underpinning the Drakes Bay Oyster Company DEIS in November 2011 and recommended further analysis of the NPS photographs for use in characterizing rates and consequences of seal disturbance (Marine Mammal Commission, 2011). In response to that recommendation, the NPS asked the U.S. Geological Survey (USGS) to conduct an independent review of the photographs and render an opinion on the utility of the remote camera data for informing the environmental impact analyses included in the DEIS.\n\nIn consultation with the NPS, we selected the 2008 photographic dataset for detailed evaluation because it covers a full harbor seal breeding season (March 1 to June 30), provides two fields of view (two cameras were deployed), and represents a time period when cameras were most consistently deployed and maintained. The NPS requested that the photographs be evaluated in absence of other data or information pertaining to seal and human activity in the estuary and that we focus on the extent to which the photographs could be used in understanding the relationship between human activity (including commercial oyster production) and harbor seal disturbance and distribution in the estuary.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121249","usgsCitation":"Lellis, W.A., Blakeslee, C.J., Allen, L.K., Molnia, B.F., Price, S.D., Bristol, R.S., and Stewart, B., 2012, Assessment of photographs from wildlife monitoring cameras in Drakes Estero, Point Reyes National Seashore, California: U.S. Geological Survey Open-File Report 2012-1249, iii, 24 p.; Appendix, https://doi.org/10.3133/ofr20121249.","productDescription":"iii, 24 p.; Appendix","costCenters":[{"id":410,"text":"National Center","active":false,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":263359,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1249.jpg"},{"id":263355,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1249/"},{"id":263356,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1249/pdf/OFR2012-1249.pdf"}],"country":"United States","state":"California","otherGeospatial":"Drakes Estero;Point Reyes National Seashore","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50b48f7de4b0b3fb1a229134","contributors":{"authors":[{"text":"Lellis, William A. 0000-0001-7806-2904 wlellis@usgs.gov","orcid":"https://orcid.org/0000-0001-7806-2904","contributorId":2369,"corporation":false,"usgs":true,"family":"Lellis","given":"William","email":"wlellis@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":469137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakeslee, Carrie J. 0000-0002-0801-5325 cblakeslee@usgs.gov","orcid":"https://orcid.org/0000-0002-0801-5325","contributorId":5462,"corporation":false,"usgs":true,"family":"Blakeslee","given":"Carrie","email":"cblakeslee@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":469142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Laurie K. lkallen@usgs.gov","contributorId":5134,"corporation":false,"usgs":true,"family":"Allen","given":"Laurie","email":"lkallen@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":469141,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Molnia, Bruce F. bmolnia@usgs.gov","contributorId":4002,"corporation":false,"usgs":true,"family":"Molnia","given":"Bruce","email":"bmolnia@usgs.gov","middleInitial":"F.","affiliations":[{"id":410,"text":"National Center","active":false,"usgs":true}],"preferred":false,"id":469140,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Price, Susan D. sprice@usgs.gov","contributorId":3825,"corporation":false,"usgs":true,"family":"Price","given":"Susan","email":"sprice@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":469139,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bristol, R. Sky 0000-0003-1682-4031 sbristol@usgs.gov","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":3585,"corporation":false,"usgs":true,"family":"Bristol","given":"R.","email":"sbristol@usgs.gov","middleInitial":"Sky","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":469138,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stewart, Brent","contributorId":69862,"corporation":false,"usgs":true,"family":"Stewart","given":"Brent","email":"","affiliations":[],"preferred":false,"id":469143,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70040860,"text":"sir20125164 - 2012 - Global exploration and production capacity for platinum-group metals from 1995 through 2015","interactions":[],"lastModifiedDate":"2012-12-20T08:59:45","indexId":"sir20125164","displayToPublicDate":"2012-11-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5164","title":"Global exploration and production capacity for platinum-group metals from 1995 through 2015","docAbstract":"Platinum-group metals (PGMs) are required in a variety of commercial, industrial, and military applications for many existing and emerging technologies, yet the United States is highly dependent on foreign sources of PGMs. Information on global exploration for PGMs since 1995 has been used in this study as a basis for identifying locations where the industry has determined that exploration has provided data sufficient to warrant development of a new mine or expansion of an existing operation or where a significant increase in capacity for PGMs is anticipated by 2015. Discussions include an overview of the industry and the selected sites, factors affecting mineral supply, and circumstances leading to the development of mineral properties with the potential to affect mineral supply. Of the 52 sites or regional operations that were considered in this analysis, 16 sites were producing before 1995, 28 sites commenced production from 1995 through 2010, and 8 sites were expected to begin production from 2011 through 2015 if development plans came to fruition. The United States imports PGMs primarily from Canada, Russia, South Africa, and Zimbabwe to meet increasing demand for these materials in a variety of specialized and high-tech applications. Feed sources of PGMs are changing in South Africa and Russia, which together accounted for about 89 percent of platinum production and 82 percent of palladium production in 2009. A greater amount of South African PGM capacity is likely to come from deeper, higher cost Upper Group Reef seam 2 deposits and deposits in the Eastern Bushveld area. Future Russian PGM capacity is likely to come from ore zones with generally lower PGM content and different platinum-to-palladium ratios than the nickel-rich ore that dominated PGM supply in the 1990s. Because PGM supply from Canada and Russia is derived as a byproduct of copper and nickel mining, the PGM supply from these countries is influenced by economic, environmental, political, and technological factors affecting exploration for and development of copper and nickel, as well as factors affecting the PGM industry. The recovery of PGMs from mill tailings since 2004 and the recycling of PGMs from catalytic converters, electrical components, and jewelry has increased since 1995 so that recycled PGMs recovered from these products accounted for about 30 percent of the supply of platinum worldwide and 29 percent of the supply of palladium worldwide in 2010. Economic and geopolitical conditions have influenced PGM supply and demand. The global recession of 2008 and 2009 temporarily decreased demand for PGMs and constrained PGM mine exploration and development, at least through 2010. Legislation regulating the structure of the mining sector has affected mining in Russia, South Africa, and Zimbabwe. Stricter vehicle emissions standards in established markets since the 1980s have led to mandatory use of pollution control devices, such as catalytic converters, that contain PGMs and are required on vehicles in expanding markets, such as China and India. It is expected that South Africa, Russia, Canada, and Zimbabwe will continue to be the principal sources of PGM at least for the next decade. Based on this review of the PGM industry, the world’s platinum capacity, expressed in terms of recoverable platinum metal, increased from 1995 through 2010 by 77,000 kilograms (kg) in South Africa, 9,000 kg in Zimbabwe, 6,000 kg in Russia, 2,000 kg in Botswana, and 2,000 kg in Canada. For the same period, palladium capacity worldwide increased by 44,000 kg in South Africa, 22,000 kg in Russia, 8,000 kg in Canada, 8,000 kg in the United States, 7,000 kg in Zimbabwe, and 3,000 kg in Botswana. Platinum capacity worldwide is expected to further increase by 24,000 kg in South Africa, 9,000 kg in Russia, 3,000 kg in Canada, and 2,000 kg in Zimbabwe from 2011 through 2015. Palladium capacity worldwide is likewise expected to increase an additional 16,000 kg in Russia, 14,000 kg in South Africa, 4,000 kg in Zimbabwe, and 1,000 kg in Canada if new or expanded mine and associated processing capacity comes into production as planned. It is likely that the magnitude of these changes in PGM capacity has been influenced by such factors as the global economy, electrical capacity shortages and mine safety concerns in South Africa, and geopolitical conditions in the major PGM producing countries.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125164","usgsCitation":"Wilburn, D.R., 2012, Global exploration and production capacity for platinum-group metals from 1995 through 2015 (Originally posted November 26, 2012; Revised December 14, 2012): U.S. Geological Survey Scientific Investigations Report 2012-5164, iv, 26 p., https://doi.org/10.3133/sir20125164.","productDescription":"iv, 26 p.","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1995-01-01","temporalEnd":"2015-12-31","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":264658,"type":{"id":18,"text":"Project Site"},"url":"https://minerals.usgs.gov/minerals/"},{"id":263371,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5164/"},{"id":263372,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5164/pdf/sir2012-5164.pdf"},{"id":263373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5164.gif"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","edition":"Originally posted November 26, 2012; Revised December 14, 2012","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50b48f8ae4b0b3fb1a229140","contributors":{"authors":[{"text":"Wilburn, David R. 0000-0002-5371-7617 wilburn@usgs.gov","orcid":"https://orcid.org/0000-0002-5371-7617","contributorId":1755,"corporation":false,"usgs":true,"family":"Wilburn","given":"David","email":"wilburn@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":469151,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70040857,"text":"sir20125256 - 2012 - Alluvial diamond resource potential and production capacity assessment of Guinea","interactions":[],"lastModifiedDate":"2022-05-27T15:40:31.211434","indexId":"sir20125256","displayToPublicDate":"2012-11-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5256","title":"Alluvial diamond resource potential and production capacity assessment of Guinea","docAbstract":"In May of 2000, a meeting was convened in Kimberley, South Africa, by representatives of the diamond industry and leaders of African governments to develop a certification process intended to assure that export shipments of rough diamonds were free of conflict concerns. Outcomes of the meeting were formally supported later in December of 2000 by the United Nations in a resolution adopted by the General Assembly. By 2002, the Kimberley Process Certification Scheme (KPCS) was ratified and signed by diamond-producing and diamond-importing countries. The goal of this study was to estimate the alluvial diamond resource endowment and the current production capacity of the alluvial diamond mining sector of Guinea. A modified volume and grade methodology was used to estimate the remaining diamond reserves within Guinea's diamondiferous regions, while the diamond-production capacity of these zones was estimated by inputting the number of artisanal miners, the number of days artisans work per year, and the average grade of the deposits into a formulaic expression. Guinea's resource potential was estimated to be approximately 40 million carats, while the production capacity was estimated to lie within a range of 480,000 to 720,000 carats per year. While preliminary results have been produced by integrating historical documents, five fieldwork campaigns, and remote sensing and GIS analysis, significant data gaps remain. The artisanal mining sector is dynamic and is affected by a variety of internal and external factors. Estimates of the number of artisans and deposit variables, such as grade, vary from site to site and from zone to zone. This report has been developed on the basis of the most detailed information available at this time. However, continued fieldwork and evaluation of artisanally mined deposits would increase the accuracy of the results.","language":"English, French","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125256","collaboration":"Prepared in cooperation with the Ministère des Mines et de la Géologie of Guinea under the auspices of the U.S. Department of State","usgsCitation":"Chirico, P., Malpeli, K., Van Bockstael, M., Diaby, M., Cisse, K., Diallo, T.A., and Sano, M., 2012, Alluvial diamond resource potential and production capacity assessment of Guinea (Originally posted November 26, 2012; French Translation April 30, 2014): U.S. Geological Survey Scientific Investigations Report 2012-5256, vi, 49 p., https://doi.org/10.3133/sir20125256.","productDescription":"vi, 49 p.","numberOfPages":"59","additionalOnlineFiles":"N","costCenters":[{"id":240,"text":"Eastern Earth Surface Processes Team","active":false,"usgs":true}],"links":[{"id":263366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125256.gif"},{"id":263364,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5256/","linkFileType":{"id":5,"text":"html"}},{"id":263365,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5256/pdf/sir2012-5256.pdf","text":"Report (English)","linkFileType":{"id":1,"text":"pdf"}},{"id":286835,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5256/french/pdf/sir2012-5256_frenchversion.pdf","text":"Report (French)","linkFileType":{"id":1,"text":"pdf"}}],"country":"Guinea","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -15.0,7.0 ], [ -15.0,13.0 ], [ -7.25,13.0 ], [ -7.25,7.0 ], [ -15.0,7.0 ] ] ] } } ] }","edition":"Originally posted November 26, 2012; French Translation April 30, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50b48f69e4b0b3fb1a22912c","contributors":{"authors":[{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":469146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":469148,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Bockstael, Mark","contributorId":8351,"corporation":false,"usgs":true,"family":"Van Bockstael","given":"Mark","email":"","affiliations":[],"preferred":false,"id":469144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diaby, Mamadou","contributorId":50057,"corporation":false,"usgs":true,"family":"Diaby","given":"Mamadou","email":"","affiliations":[],"preferred":false,"id":469147,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cisse, Kabinet","contributorId":66140,"corporation":false,"usgs":true,"family":"Cisse","given":"Kabinet","email":"","affiliations":[],"preferred":false,"id":469149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diallo, Thierno Amadou","contributorId":80987,"corporation":false,"usgs":true,"family":"Diallo","given":"Thierno","email":"","middleInitial":"Amadou","affiliations":[],"preferred":false,"id":469150,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sano, Mahmoud","contributorId":23406,"corporation":false,"usgs":true,"family":"Sano","given":"Mahmoud","email":"","affiliations":[],"preferred":false,"id":469145,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70182150,"text":"70182150 - 2012 - Soil-water dynamics and unsaturated storage during snowmelt following wildfire","interactions":[],"lastModifiedDate":"2017-02-17T10:02:03","indexId":"70182150","displayToPublicDate":"2012-11-22T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Soil-water dynamics and unsaturated storage during snowmelt following wildfire","docAbstract":"Many forested watersheds with a substantial fraction of precipitation delivered as snow have the potential for landscape disturbance by wildfire. Little is known about the immediate effects of wildfire on snowmelt and near-surface hydrologic responses, including soil-water storage. Montane systems at the rain-snow transition have soil-water dynamics that are further complicated during the snowmelt period by strong aspect controls on snowmelt and soil thawing. Here we present data from field measurements of snow hydrology and subsurface hydrologic and temperature responses during the first winter and spring after the September 2010 Fourmile Canyon Fire in Colorado, USA. Our observations of soil-water content and soil temperature show sharp contrasts in hydrologic and thermal conditions between north- and south-facing slopes. South-facing burned soils were ∼1–2 °C warmer on average than north-facing burned soils and ∼1.5 °C warmer than south-facing unburned soils, which affected soil thawing during the snowmelt period. Soil-water dynamics also differed by aspect: in response to soil thawing, soil-water content increased approximately one month earlier on south-facing burned slopes than on north-facing burned slopes. While aspect and wildfire affect soil-water dynamics during snowmelt, soil-water storage at the end of the snowmelt period reached the value at field capacity for each plot, suggesting that post-snowmelt unsaturated storage was not substantially influenced by aspect in wildfire-affected areas. Our data and analysis indicate that the amount of snowmelt-driven groundwater recharge may be larger in wildfire-impacted areas, especially on south-facing slopes, because of earlier soil thaw and longer durations of soil-water contents above field capacity in those areas.
","language":"English","publisher":"European Geophysical Society","publisherLocation":"Katlenburg-Lindau","doi":"10.5194/hess-16-1401-2012","usgsCitation":"Ebel, B.A., Hinckley, E., and Martin, D.A., 2012, Soil-water dynamics and unsaturated storage during snowmelt following wildfire: Hydrology and Earth System Sciences, v. 16, p. 1401-1417, https://doi.org/10.5194/hess-16-1401-2012.","productDescription":"17 p.","startPage":"1401","endPage":"1417","ipdsId":"IP-034382","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":474259,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-16-1401-2012","text":"Publisher Index Page"},{"id":335802,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-05-15","publicationStatus":"PW","scienceBaseUri":"58a819b8e4b025c46429afd0","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":669794,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hinckley, E.S.","contributorId":181852,"corporation":false,"usgs":false,"family":"Hinckley","given":"E.S.","email":"","affiliations":[],"preferred":false,"id":669824,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":168662,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":669795,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041250,"text":"ds709E - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:14:45","indexId":"ds709E","displayToPublicDate":"2012-11-21T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"E","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Aynak mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2008,2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Aynak) and the WGS84 datum. The final image mosaics were subdivided into four overlapping tiles or quadrants because of the large size of the target area. The four image tiles (or quadrants) for the Aynak area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Aynak study area, five subareas were designated for detailed field investigations (that is, the Bakhel-Charwaz, Kelaghey-Kakhay, Kharuti-Dawrankhel, Logar Valley, and Yagh-Darra/Gul-Darra subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709E","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., Cagney, L.E., Arko, S.A., and Harbin, M., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Aynak mineral district in Afghanistan: Chapter E in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 3 Maps: 11 x 8.5 inches and 42.79 x 29.78 inches; 18 Image Files; 18 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709E.","productDescription":"Readme; 3 Maps: 11 x 8.5 inches and 42.79 x 29.78 inches; 18 Image Files; 18 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":263605,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_E.jpg"},{"id":263595,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/e/"},{"id":263600,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/e/index_maps/Aynak_Subarea_Image_Index_Map.pdf"},{"id":263601,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/e/image_files/image_files.html"},{"id":263597,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/e/1_readme.txt"},{"id":263598,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/e/index_maps/Aynak_Area-of-Interest_Index_Map.pdf"},{"id":263599,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/e/index_maps/Aynak_Image_Index_Map.pdf"},{"id":263602,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/e/metadata/metadata.html"},{"id":263603,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/e/shapefiles/shapefiles.html"},{"id":263604,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/"}],"country":"Afghanistan","state":"Kabul;Logar;Paktya;Wardak","otherGeospatial":"Aynak Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 68.633333,34.083333 ], [ 68.633333,34.533333 ], [ 69.5,34.533333 ], [ 69.5,34.083333 ], [ 68.633333,34.083333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bd1396e4b069d93eefc4ec","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":469455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":469456,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":469458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":469457,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70041372,"text":"ds709F - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:14:25","indexId":"ds709F","displayToPublicDate":"2012-11-21T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"F","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Badakhshan mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency ((c)JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Badakhshan) and the WGS84 datum. The final image mosaics were subdivided into six overlapping tiles or quadrants because of the large size of the target area. The six image tiles (or quadrants) for the Badakhshan area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Badakhshan study area, three subareas were designated for detailed field investigations (that is, the Bharak, Fayz-Abad, and Ragh subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709F","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., Arko, S.A., and Harbin, M., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Badakhshan mineral district in Afghanistan: Chapter F in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 3 Maps: 11 x 8.5 inches and 45.64 x 48.46 inches; 18 Image Files; 18 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709F.","productDescription":"Readme; 3 Maps: 11 x 8.5 inches and 45.64 x 48.46 inches; 18 Image Files; 18 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":263684,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_F.jpg"},{"id":263675,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/f/"},{"id":263676,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/f/1_readme.txt"},{"id":263677,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/f/index_maps/Badakhshan_Area-of-Interest_Index_Map.pdf"},{"id":263678,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/f/index_maps/Badakhshan_Image_Mosaic_Index_Map.pdf"},{"id":263679,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/f/index_maps/Badakhshan_Subarea_Image_Mosaic_Index_Map.pdf"},{"id":263680,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/f/image_files/image_files.html"},{"id":263681,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/f/metadata/metadata.html"},{"id":263682,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/f/shapefiles/shapefiles.html"},{"id":263683,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"}],"country":"Afghanistan","state":"Badakhshan","otherGeospatial":"Badakhshan Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 70.25,37.0 ], [ 70.25,37.75 ], [ 71.25,37.75 ], [ 71.25,37.0 ], [ 70.25,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bfbda6e4b01744973f7813","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":469650,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":469652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":469651,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70040830,"text":"fs20123130 - 2012 - Summary of the reconnaissance investigation of the diamond resource potential and production capacity of Côte d’Ivoire","interactions":[],"lastModifiedDate":"2012-11-20T10:02:31","indexId":"fs20123130","displayToPublicDate":"2012-11-20T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-3130","title":"Summary of the reconnaissance investigation of the diamond resource potential and production capacity of Côte d’Ivoire","docAbstract":"This study presents the results of a multiyear effort to monitor the diamond mining activities of Côte d’Ivoire’s two main diamond regions, Séguéla and Tortiya. The innovative approach developed for this study integrates archival reports and maps, high-resolution satellite imagery, and terrain modeling to assess the diamond resource potential and production capacity of the Séguéla and Tortiya deposits.\n\nA geologic resource assessment was conducted to calculate the remaining diamond reserves for Séguéla and Tortiya using archival geologic data, including gravel grade and thickness recorded by the Ivorian mining company Société pour le Développement Minier (SODEMI). These data were combined with terrain analysis and geomorphological maps in a geological process-driven model. After accounting for previous production, a total of 10,100,000 carats are estimated to be remaining in Séguéla and a total of 1,100,000 carats are estimated to be remaining in Tortiya, based on currently known deposits.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123130","collaboration":"Prepared under the auspices of the U.S. Department of State","usgsCitation":"Chirico, P., and Malpeli, K., 2012, Summary of the reconnaissance investigation of the diamond resource potential and production capacity of Côte d’Ivoire: U.S. Geological Survey Fact Sheet 2012-3130, 2 p., https://doi.org/10.3133/fs20123130.","productDescription":"2 p.","startPage":"1","endPage":"2","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":229,"text":"Earth Surface Processes Team","active":false,"usgs":true}],"links":[{"id":263298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3130.gif"},{"id":263296,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3130/pdf/fs2012-3130.pdf"},{"id":263297,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3130/"}],"otherGeospatial":"C�te D�ivoire;Ivory Coast","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -8.6,4.35 ], [ -8.6,10.74 ], [ -2.49,10.74 ], [ -2.49,4.35 ], [ -8.6,4.35 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50abfb8ee4b0afbc75eb981c","contributors":{"authors":[{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":469089,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":469090,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70040828,"text":"fs20123129 - 2012 - Summary of the diamond resource potential and production capacity assessment of Guinea","interactions":[],"lastModifiedDate":"2012-11-20T09:48:49","indexId":"fs20123129","displayToPublicDate":"2012-11-20T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-3129","title":"Summary of the diamond resource potential and production capacity assessment of Guinea","docAbstract":"In May of 2000, a meeting was convened in Kimberley, South Africa, by representatives of the diamond industry and leaders of African governments to develop a certification process intended to assure that export shipments of rough diamonds were free of conflict concerns. Outcomes of the meeting were formally supported later in December of 2000 by the United Nations in a resolution adopted by the General Assembly. By 2002, the Kimberley Process Certification Scheme (KPCS) was ratified and signed by diamond-producing and diamond-importing countries. As of August 2012, the Kimberley Process (KP) had 51 participants representing 77 countries. With the passing of the AD, the Plenary agreed that further efforts should be made to assess Guinea's diamond production capacity. In support of this objective, the U.S. Geological Survey (USGS) partnered with the Kimberley Process Working Group of Diamond Experts (WGDE) and Guinea's Ministry of Mines and Geology (MMG) to conduct a field campaign in Guinea from April 24 through May 2, 2010. The field team was composed of Mark Van Bockstael of the WGDE, Peter Chirico of the USGS, and several geologists from the MMG. The team visited diamond mining sites in western Guinea's Kindia, Forècariah, Coyah, and Tèlimèlè Prefectures, in which the Guinean government identified newly discovered deposits mined by artisans. Several mining sites within the Kissidougou Prefecture in southeastern Guinea were also visited as part of this study. Geologic and geomorphic information on the diamond deposits was collected at each site. The fieldwork conducted during this trip served as a means of acquiring critical data needed to conduct a full assessment of diamond resources and production capacity.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123129","collaboration":"Prepared under the auspices of the U.S. Department of State","usgsCitation":"Chirico, P., and Malpeli, K., 2012, Summary of the diamond resource potential and production capacity assessment of Guinea: U.S. Geological Survey Fact Sheet 2012-3129, 2 p., https://doi.org/10.3133/fs20123129.","productDescription":"2 p.","numberOfPages":"2","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":263295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3129.gif"},{"id":263293,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3129/"},{"id":263294,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3129/pdf/fs2012-3129.pdf"}],"country":"Guinea;West Africa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -15.0,6.0 ], [ -15.0,13.0 ], [ -7.0,13.0 ], [ -7.0,6.0 ], [ -15.0,6.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50abfb89e4b0afbc75eb9818","contributors":{"authors":[{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":469087,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":469088,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}